An automated histological classification system for precision diagnostics of kidney allografts

Daniel Yoo, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Valentin Goutaudier, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Gillian Divard, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Juliette Gueguen, Néphrologie-Immunologie Clinique, Hôpital Bretonneau, CHU Tours, Tours, France.
Brad C. Astor, Division of Nephrology, Department of Medicine, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Olivier Aubert, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Marc Raynaud, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Zeynep Demir, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Julien Hogan, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Patricia Weng, Pediatric Nephrology, David Geffen School of Medicine at UCLA, UCLA Mattel Children's Hospital, Los Angeles, CA, USA.
Jodi Smith, Department of Pediatrics, University of Washington School of Medicine, Seattle Children's Hospital, Seattle, WA, USA.
Rouba Garro, Division of Pediatric Nephrology, Emory University School of Medicine, Children's Pediatric Institute, Atlanta, GA, USA.
Bradley A. Warady, Division of Pediatric Nephrology, University of Kansas City, Children's Mercy Hospital, Kansas City, MO, USA.
Rima S. Zahr, Division of Pediatric Nephrology and Hypertension, University of Tennessee Health Science Center, Le Bonheur Children's Hospital, Memphis, TN, USA.
Marta Sablik, Université Paris Cité, INSERM U970, Paris Institute for Transplantation and Organ Regeneration, Paris, France.
Katherine Twombley, Acute Dialysis Units, Pediatric Kidney Transplant, Medical University of South Carolina, Charleston, SC, USA.
Lionel Couzi, Department of Nephrology, Transplantation, Dialysis and Apheresis, CHU Bordeaux, Bordeaux, France.
Thierry Berney, Division of Abdominal and Transplantation Surgery, Department of Surgery, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland.
Olivia Boyer, Division of Pediatric Nephrology, Necker Hospital, Université Paris Cité, Paris, France.
Jean-Paul Duong-Van-Huyen, Department of Pathology, Necker-Enfants Malades Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France.
Magali Giral, Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, Nantes, France.
Alaa Alsadi, Department of Pathology, University of Wisconsin, Madison, WI, USA.
Pierre A. Gourraud, Nantes Université, CHU Nantes, INSERM, Center for Research in Transplantation and Translational Immunology, UMR 1064, ITUN, Nantes, France.
Emmanuel Morelon, Department of Transplantation, Edouard Herriot University Hospital, Hospices Civils de Lyon, University Lyon, University of Lyon I, Lyon, France.
Moglie Le Quintrec, Department of Nephrology, Centre Hospitalier Universitaire Montpellier, Montpellier, France.

Abstract

For three decades, the international Banff classification has been the gold standard for kidney allograft rejection diagnosis, but this system has become complex over time with the integration of multimodal data and rules, leading to misclassifications that can have deleterious therapeutic consequences for patients. To improve diagnosis, we developed a decision-support system, based on an algorithm covering all classification rules and diagnostic scenarios, that automatically assigns kidney allograft diagnoses. We then tested its ability to reclassify rejection diagnoses for adult and pediatric kidney transplant recipients in three international multicentric cohorts and two large prospective clinical trials, including 4,409 biopsies from 3,054 patients (62.05% male and 37.95% female) followed in 20 transplant referral centers in Europe and North America. In the adult kidney transplant population, the Banff Automation System reclassified 83 out of 279 (29.75%) antibody-mediated rejection cases and 57 out of 105 (54.29%) T cell-mediated rejection cases, whereas 237 out of 3,239 (7.32%) biopsies diagnosed as non-rejection by pathologists were reclassified as rejection. In the pediatric population, the reclassification rates were 8 out of 26 (30.77%) for antibody-mediated rejection and 12 out of 39 (30.77%) for T cell-mediated rejection. Finally, we found that reclassification of the initial diagnoses by the Banff Automation System was associated with an improved risk stratification of long-term allograft outcomes. This study demonstrates the potential of an automated histological classification to improve transplant patient care by correcting diagnostic errors and standardizing allograft rejection diagnoses.ClinicalTrials.gov registration: NCT05306795 .